Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session Q09: Cavitation and Multiphase Flows
12:50 PM–3:26 PM,
Tuesday, November 20, 2018
Georgia World Congress Center
Room: B214
Chair: Aren Hellum, Naval Undersea Warfare Center
Abstract ID: BAPS.2018.DFD.Q09.1
Abstract: Q09.00001 : Predicting Cavitation Erosion Propensity and Severity in Fuel Injection Systems*
12:50 PM–1:03 PM
Presenter:
Gina Maureen Magnotti
(Argonne National Laboratory)
Authors:
Gina Maureen Magnotti
(Argonne National Laboratory)
Michele Battistoni
(Università degli Studi di Perugia)
Kaushik Saha
(Indian Institute of Technology Delhi)
Sibendu Som
(Argonne National Laboratory)
The objective of this work is to identify computational metrics that can characterize the erosive potential of cavitation within injector orifices. While a commonly employed cavitation erosion metric, namely the maximum local pressure, was found to describe single impact events, no additional information could be determined regarding the material erosion process. To improve representation of the incubation period, a new metric was derived based on the cumulative energy absorbed by the solid material from repeated hydrodynamic impacts. The stored energy metric was then implemented into CONVERGE. Large eddy simulations for turbulent cavitating flow through channel geometries were performed, where the multiphase and multi-component flow was represented using a homogeneous mixture modeling approach. Through comparison against available experimental data, the stored energy metric was found to accurately predict the influence of flow conditions on the incubation period before material erosion. Additionally, detailed analysis of cavitation cloud collapse events highlighted the strong correlation between cloud collapse mechanisms and their erosive potential.
*Argonne National Laboratory’s work was supported by the U.S Department of Energy under contract DE-AC02-06CH11357.
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.Q09.1
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